Least Squares Support Vector Machine Classi ers : a Large Scale Algorithm

@inproceedings{Suykens1999LeastSS,
  title={Least Squares Support Vector Machine Classi ers : a Large Scale Algorithm},
  author={Johan A. K. Suykens and Lukas Lukas and Paul Van Dooren and Bart De Moor and Joos Vandewalle and K. U. Leuven and Kardinaal Mercierlaan},
  year={1999}
}
Support vector machines (SVM's) have been introduced in literature as a method for pattern recognition and function estimation, within the framework of statistical learning theory and structural risk minimization. A least squares version (LS-SVM) has been recently reported which expresses the training in terms of solving a set of linear equations instead of quadratic programming as for the standard SVM case. In this paper we present an iterative training algorithm for LS-SVM's which is based on… CONTINUE READING
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